Interactive and Dynamic Graphics for Data Analysis

This richly illustrated book describes the use of interactive and dynamic graphics as part of multidimensional data analysis. Chapter topics include clustering, supervised classification, and working with missing values. A variety of plots and interaction methods are used in each analysis, often starting with brushing linked low-dimensional views and working up to manual manipulation of tours of several variables. The book is augmented by a wealth of online material.

From the reviews: "The central theme of the book is multivariate data visualization. The focus is on interactive and dynamic graphics.… The target audience of the book is (advanced) undergraduate and graduate students, but also industrial statisticians, engineers, bioinformaticists, and computer scientists.… Each chapter ends with some exercises. The chapters are well written and structured, and the examples are well documented.… A reader with a decent knowledge of multivariate statistics … will be happy with this book." (Ruud H. Koning, Kwantitatieve Methoden, 2008R14) "In this book, R commands are used to exploit the power of the GGobi systems for interactive and dynamic graphics.…This book, … is a very useful brief overview of the insight that a powerful modern suite of graphics tools may offer." (John Maindonald, International Statistical Review, 2008, 76, 3, pages 436-437) "Diane Cook and Deborah Swayne’s new book, part of Springer’s Use R! series, helps fill an important niche in the literature for the R community and readers of Biometrics. The title of the book indicates the substantial challenge: the book is neither purely methodological nor simply about software. It draws upon the expertise of a wide range of contributors.… I will borrow a phrase the authors use on the opening page: these resources help us "orient ourselves in the sea of information."" (Biometrics 2008) "The book describes the use of interactive and dynamic graphics as part of multidimensional data analysis. … The book may be used as a text in a class on statistical graphics, exploratory data analysis, visual data mining, or information visualisation. It might also be used as an adjunct text in a course on multivariate data analysis or data mining. Moreover, the book is suitable for an industrial statistician, engineer, bioinformaticist, or computer scientist … . Finally, it may be useful to a mathematician … ." (Christina Diakaki, Zentralblatt MATH, Vol. 1154, 2009)